diff --git a/docs/source/installation/build-from-source-linux.md b/docs/source/installation/build-from-source-linux.md
index 19dab71c769..7b94aa88119 100644
--- a/docs/source/installation/build-from-source-linux.md
+++ b/docs/source/installation/build-from-source-linux.md
@@ -147,6 +147,11 @@ check <https://github.com/NVIDIA/TensorRT-LLM/tree/main/docker>.
 
 ## Build TensorRT LLM
 
+```{tip}
+:name: build-from-source-tip-cuda-version
+TensorRT LLM 1.1 supports both CUDA 12.9 and 13.0 while some dependency changes are required. The `requirements.txt` contains dependencies needed by CUDA 13.0. If you are using CUDA 12.9, please uncomment lines end with `# <For CUDA 12.9>` and comment out the next lines.
+```
+
 ### Option 1: Full Build with C++ Compilation
 
 The following command compiles the C++ code and packages the compiled libraries along with the Python files into a wheel. When developing C++ code, you need this full build command to apply your code changes.
diff --git a/docs/source/installation/linux.md b/docs/source/installation/linux.md
index 02a0cf7817d..68db9403d3d 100644
--- a/docs/source/installation/linux.md
+++ b/docs/source/installation/linux.md
@@ -12,6 +12,11 @@
    Install CUDA Toolkit following the [CUDA Installation Guide for Linux](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) and
    make sure `CUDA_HOME` environment variable is properly set.
 
+   ```{tip}
+   :name: installation-linux-tip-cuda-version
+   TensorRT LLM 1.1 supports both CUDA 12.9 and 13.0. The wheel package release only supports CUDA 12.9, while CUDA 13.0 is only supported through NGC container release.
+   ```
+
    ```bash
    # Optional step: Only required for NVIDIA Blackwell GPUs and SBSA platform
    pip3 install torch==2.7.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128